In hydrocarbon system evaluations, data interpretation and processing (including mapping horizons, faults and fault networks) is essential to determine the reservoirs and migration pathways from the source to the reservoir. Faults can also help trap hydrocarbons or fragment a reservoir and therefore cause complications during field production.
Data interpretation and processing commonly requires identification and/or processing of certain defined regions within the entire data set. For example, for processing geologically defined regions identification of regions constrained by horizons or faults of interest is typically required. Effective visualization of regions (or subsets) within the data set during interpretation is improved through interactive modification of region constraints, displayed opacity, and/or displayed color scale.
A sample in a three-dimensional data set can be represented by, for example, 8-bit, 16-bit or 32-bit data storage. A bit is a binary representation carrying the value of either 1 or 0. The higher the number of bits, the better the sample precision. Several methods have been used to define and process data subsets via the representation of samples in a data set.
One method requires altering the bit representation of the data sample. For example, if a three-dimensional sample belongs (or does not belong) to a particular geological region, then the bit representing this sample would be set to 1 (or 0). This method is used by many volume visualization systems, including a commercial package called VoxelGeo™. This method allows rapid identification of a region during volume rendering and processing by checking the bits of the data samples. One disadvantage of this method is that the sample precision is reduced, since one of the bits in each sample is used for the region identifier (for example, 8-bit sample reduced to 7-bit). Another limitation is that only one region can be represented at a time. This limitation requires that for a second region to be analyzed, a time-consuming reprocessing of the entire data set in order to reset the bits according to the new region's constraints is required.
A second method, also used by commercially available products (such as, Gocad™), is to represent the region using a separate three-dimensional data volume (called a bit volume) with the same dimensionality as the original. The number of bits at each point in the bit volume depends on the size of the data storage. This bit volume uses one bit at each sample location to indicate region membership of the sample in the corresponding data set. Therefore, 8-bit data can indicate membership of up to eight different regions. This method can identify a region during volume rendering and processing. Volume rendering techniques utilize the graphic device's texture memory and display engine on a computer station to display three-dimensional volumetric information. Most volume rendering techniques employ texture memory transfer functions, which assign colors (red, green and blue), and opacity values to each data element of a given data set. The method requires checking the bit in the bit volume and processing the corresponding data sample from the original data volume.
The second method differs from the first method as different bit volumes can represent different regions without modification of the original data sample. Applying gated-logic (or Boolean-logic) constraints to several bit volumes can derive a new bit volume that characterizes all the previous bit volumes as one bit volume. Boolean-logic is a form of symbolic logic, which provides a mathematical procedure for manipulating logical relationships in symbolic form. This method allows multiple geological regions to be created. However, each new bit volume derived by application of gated logical operations to existing constraints requires expensive computational time and data storage.
Currently, to identify regions of interest (such as, regions constrained by horizons or faults of interest) in seismic volumes requires a time-consuming processing step to “sculpt” the data volumes. Sculpting currently requires use of individual bits to control the processing or rendering of a region. Combining multiple constraints (such as horizons or faults) requires the reprocessing of the entire volume using Boolean-logic to individually check each region's constraint. Modifying region constraints or creating regions based on the combination of multiple constraints, with current technology, requires vast amounts of computational resources, especially in large three-dimensional data sets. Accordingly, there is a need for an efficient and flexible way to interactively handle regions defined by multiple constraints and to apply Boolean-logic to these regions for interpretation and visualization applications.